I was amazed at the VitalSource way of presenting the books....
Everything looks perfectly typeset, but yet you can "flip"
through the book in the same way you would "flip" through a very
long web page in your web browser. And best of all, whenever I
have my tablet with me, my books are just a swipe away.

Comment from the Stata technical group

Introduction to Time Series Using Stata, by Sean Becketti, provides a
practical guide to working with time-series data using Stata and will appeal
to a broad range of users. The many examples, concise explanations that
focus on intuition, and useful tips based on the author’s decades of
experience using time-series methods make the book insightful not just for
academic users but also for practitioners in industry and government.

The book is appropriate both for new Stata users and for experienced users
who are new to time-series analysis.

Chapter 1 provides a mild yet fast-paced introduction to Stata, highlighting
all the features a user needs to know to get started using Stata for
time-series analysis. Chapter 2 is a quick refresher on regression and
hypothesis testing, and it defines key concepts such as white noise,
autocorrelation, and lag operators.

Chapter 3 begins the discussion of time series, using moving-average and
Holt–Winters techniques to smooth and forecast the data. Becketti
also introduces the concepts of trends, cyclicality, and seasonality and
shows how they can be extracted from a series. Chapter 4 focuses on using
these methods for forecasting and illustrates how the assumptions regarding
trends and cycles underlying the various moving-average and
Holt–Winters techniques affect the forecasts produced. Although these
techniques are sometimes neglected in other time-series books, they are easy
to implement, can be applied to many series quickly, often produce forecasts
just as good as more complicated techniques, and as Becketti emphasizes,
have the distinct advantage of being easily explained to colleagues and
policy makers without backgrounds in statistics.

Chapters 5 through 8 encompass single-equation time-series models. Chapter
5 focuses on regression analysis in the presence of autocorrelated
disturbances and details various approaches that can be used when all the
regressors are strictly exogenous but the errors are autocorrelated, when
the set of regressors includes a lagged dependent variable and independent
errors, and when the set of regressors includes a lagged dependent variable
and autocorrelated errors. Chapter 6 describes the ARIMA model and
Box–Jenkins methodology, and chapter 7 applies those techniques to
develop an ARIMA-based model of U.S. GDP. Chapter 7 in particular will
appeal to practitioners because it goes step by step through a real-world
example: here is my series, now how do I fit an ARIMA model to it? Chapter 8
is a self-contained summary of ARCH/GARCH modeling.

In the final portion of the book, Becketti discusses multiple-equation
models, particularly VARs and VECs. Chapter 9 focuses on VAR models and
illustrates all key concepts, including model specification, Granger
causality, impulse-response analyses, and forecasting, using a simple model
of the U.S. economy; structural VAR models are illustrated by imposing a
Taylor rule on interest rates. Chapter 10 presents nonstationary
time-series analysis. After describing nonstationarity and unit-root tests,
Becketti masterfully navigates the reader through the often-confusing task
of specifying a VEC model, using an example based on construction wages in
Washington, DC, and surrounding states. Chapter 11 concludes.

Sean Becketti is a financial industry veteran with three decades of
experience in academics, government, and private industry. He was a
developer of Stata in its infancy, and he was Editor of the Stata
Technical Bulletin, the precursor to the Stata Journal, between
1993 and 1996. He has been a regular Stata user since its inception, and he
wrote many of the first time-series commands in Stata.

Introduction to Time Series Using Stata, by Sean Becketti, is a
first-rate, example-based guide to time-series analysis and forecasting
using Stata. It can serve as both a reference for practitioners and a
supplemental textbook for students in applied statistics courses.

Table of contents

View table of contents >>

List of tables

List of figures

Preface

Acknowledgments

1 Just enough Stata

1.1 Getting started

1.1.1 Action first, explanation later
1.1.2 Now some explanation
1.1.3 Navigating the interface
1.1.4 The gestalt of Stata
1.1.5 The parts of Stata speech